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Journal of Bioinformatics and Computational Biology

Shuigeng Zhou, Phoebe Yi-Ping Chen, Hiroshi Mamitsuka
No abstract text is available yet for this article.
October 3, 2016: Journal of Bioinformatics and Computational Biology
Li Gu, Lichun Xue, Qi Song, Fengji Wang, Huaqin He, Zhongyi Zhang
During commercial transactions, the quality of flue-cured tobacco leaves must be characterized efficiently, and the evaluation system should be easily transferable across different traders. However, there are over 3000 chemical compounds in flue-cured tobacco leaves; thus, it is impossible to evaluate the quality of flue-cured tobacco leaves using all the chemical compounds. In this paper, we used Support Vector Machine (SVM) algorithm together with 22 chemical compounds selected by ReliefF-Particle Swarm Optimization (R-PSO) to classify the fragrant style of flue-cured tobacco leaves, where the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) were 90...
September 9, 2016: Journal of Bioinformatics and Computational Biology
Beichuan Deng, Seongho Kim, Hengguang Li, Elisabeth Heath, Xiang Zhang
Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC[Formula: see text][Formula: see text][Formula: see text]GC-MS) has been used to analyze multiple samples in a metabolomics study. However, due to some uncontrollable experimental conditions, such as the differences in temperature or pressure, matrix effects on samples and stationary phase degradation, there is always a shift of retention times in the two GC columns between samples. In order to correct the retention time shifts in GC[Formula: see text][Formula: see text][Formula: see text]GC-MS, the peak alignment is a crucial data analysis step to recognize the peaks generated by the same metabolite in different samples...
September 9, 2016: Journal of Bioinformatics and Computational Biology
Ana B Pavel, Cristian I Vasile
Cancer is a complex and heterogeneous genetic disease. Different mutations and dysregulated molecular mechanisms alter the pathways that lead to cell proliferation. In this paper, we explore a method which classifies genes into oncogenes (ONGs) and tumor suppressors. We optimize this method to identify specific (ONGs) and tumor suppressors for breast cancer, lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and colon adenocarcinoma (COAD), using data from the cancer genome atlas (TCGA). A set of genes were previously classified as ONGs and tumor suppressors across multiple cancer types (Science 2013)...
August 31, 2016: Journal of Bioinformatics and Computational Biology
Fangzhou Shen, Jian Li, Ying Zhu, Zhuo Wang
Cancer cells have different metabolism in contrast to normal cells. The advancement in omics measurement technology enables the genome-wide characterization of altered cellular processes in cancers, but the metabolic flux landscape of cancer is still far from understood. In this study, we compared the well-reconstructed tissue-specific models of five cancers, including breast, liver, lung, renal, and urothelial cancer, and their corresponding normal cells. There are similar patterns in majority of significantly regulated pathways and enriched pathways in correlated reaction sets...
August 29, 2016: Journal of Bioinformatics and Computational Biology
Jinwoo Park, Benjamin Hur, Sungmin Rhee, Sangsoo Lim, Min-Su Kim, Kwangsoo Kim, Wonshik Han, Sun Kim
A breast cancer subtype classification scheme, PAM50, based on genetic information is widely accepted for clinical applications. On the other hands, experimental cancer biology studies have been successful in revealing the mechanisms of breast cancer and now the hallmarks of cancer have been determined to explain the core mechanisms of tumorigenesis. Thus, it is important to understand how the breast cancer subtypes are related to the cancer core mechanisms, but multiple studies are yet to address the hallmarks of breast cancer subtypes...
August 29, 2016: Journal of Bioinformatics and Computational Biology
Wilson Wen Bin Goh, Limsoon Wong
Identifying reproducible yet relevant features is a major challenge in biological research. This is well documented in genomics data. Using a proposed set of three reliability benchmarks, we find that this issue exists also in proteomics for commonly used feature-selection methods, e.g. [Formula: see text]-test and recursive feature elimination. Moreover, due to high test variability, selecting the top proteins based on [Formula: see text]-value ranks - even when restricted to high-abundance proteins - does not improve reproducibility...
August 3, 2016: Journal of Bioinformatics and Computational Biology
Nada Abidi, Raimo Franke, Peter Findeisen, Frank Klawonn
To better understand the dynamics of the underlying processes in cells, it is necessary to take measurements over a time course. Modern high-throughput technologies are often used for this purpose to measure the behavior of cell products like metabolites, peptides, proteins, [Formula: see text]RNA or mRNA at different points in time. Compared to classical time series, the number of time points is usually very limited and the measurements are taken at irregular time intervals. The main reasons for this are the costs of the experiments and the fact that the dynamic behavior usually shows a strong reaction and fast changes shortly after a stimulus and then slowly converges to a certain stable state...
August 3, 2016: Journal of Bioinformatics and Computational Biology
Ashis Kumer Biswas, Jean X Gao
RNA-seq, the next generation sequencing platform, enables researchers to explore deep into the transcriptome of organisms, such as identifying functional non-coding RNAs (ncRNAs), and quantify their expressions on tissues. The functions of ncRNAs are mostly related to their secondary structures. Thus by exploring the clustering in terms of structural profiles of the corresponding read-segments would be essential and this fuels in our motivation behind this research. In this manuscript we proposed PR2S2Clust, Patched RNA-seq Read Segments' Structure-oriented Clustering, which is an analysis platform to extract features to prepare the secondary structure profiles of the RNA-seq read segments...
July 25, 2016: Journal of Bioinformatics and Computational Biology
Artem Petrov, Vladimir Arzhanik, Gennady Makarov, Oleg Koliasnikov
Antibodies are the family of proteins, which are responsible for antigen recognition. The computational modeling of interaction between an antigen and an antibody is very important when crystallographic structure is unavailable. In this research, we have discovered the correlation between the amino acid sequence of antibody and its specific binding characteristics on the example of the novel conservative binding motif, which consists of four residues: Arg H52, Tyr H33, Thr H59, and Glu H61. These residues are specifically oriented in the binding site and interact with each other in a specific manner...
August 2016: Journal of Bioinformatics and Computational Biology
Javier González, Alberto Muñoz, Gabriel Martos
We propose a new method to visualize gene expression experiments inspired by the latent semantic indexing technique originally proposed in the textual analysis context. By using the correspondence word-gene document-experiment, we define an asymmetric similarity measure of association for genes that accounts for potential hierarchies in the data, the key to obtain meaningful gene mappings. We use the polar decomposition to obtain the sources of asymmetry of the similarity matrix, which are later combined with previous knowledge...
August 2016: Journal of Bioinformatics and Computational Biology
Daniel Cerqueda-García, Luisa I Falcón
Microbialites and microbial mats are complex communities with high phylogenetic diversity. These communities are mostly composed of bacteria and archaea, which are the earliest living forms on Earth and relevant to biogeochemical evolution. In this study, we identified the shared metabolic pathways for uptake of inorganic C and N in microbial mats and microbialites based on metagenomic data sets. An in silico analysis for autotrophic pathways was used to trace the paths of C and N to the system, following an elementary flux modes (EFM) approach, resulting in a stoichiometric model...
August 2016: Journal of Bioinformatics and Computational Biology
Nolen Joy Perualila-Tan, Ziv Shkedy, Willem Talloen, Hinrich W H Göhlmann, Marijke Van Moerbeke, Adetayo Kasim
The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties...
August 2016: Journal of Bioinformatics and Computational Biology
Ruifeng Hu, Xiaobo Sun
Many studies have supported that long noncoding RNAs (lncRNAs) perform various functions in various critical biological processes. Advanced experimental and computational technologies allow access to more information on lncRNAs. Determining the functions and action mechanisms of these RNAs on a large scale is urgently needed. We provided lncRNATargets, which is a web-based platform for lncRNA target prediction based on nucleic acid thermodynamics. The nearest-neighbor (NN) model was used to calculate binging-free energy...
August 2016: Journal of Bioinformatics and Computational Biology
Chang-Chang Cao, Xiao Sun
To reduce the cost of large-scale re-sequencing, multiple individuals are pooled together and sequenced called pooled sequencing. Pooled sequencing could provide a cost-effective alternative to sequencing individuals separately. To facilitate the application of pooled sequencing in haplotype-based diseases association analysis, the critical procedure is to accurately estimate haplotype frequencies from pooled samples. Here we present Ehapp2 for estimating haplotype frequencies from pooled sequencing data by utilizing a database which provides prior information of known haplotypes...
August 2016: Journal of Bioinformatics and Computational Biology
Xiaoling Wang, Jingshi Han, Kui Li, Guoqing Wang, Mudong Hao
Experiments showed that bacterial biofilms are heterogeneous, for example, the density, the diffusion coefficient, and mechanical properties of the biofilm are different along the biofilm thickness. In this paper, we establish a multi-layer composite model to describe the biofilm mechanical inhomogeneity based on unified multiple-component cellular automaton (UMCCA) model. By using our model, we develop finite element simulation procedure for biofilm tension experiment. The failure limit and biofilm extension displacement obtained from our model agree well with experimental measurements...
August 2016: Journal of Bioinformatics and Computational Biology
Worrawat Engchuan, Asawin Meechai, Sissades Tongsima, Narumol Doungpan, Jonathan H Chan
Cancer is a complex disease that cannot be diagnosed reliably using only single gene expression analysis. Using gene-set analysis on high throughput gene expression profiling controlled by various environmental factors is a commonly adopted technique used by the cancer research community. This work develops a comprehensive gene expression analysis tool (gene-set activity toolbox: (GAT)) that is implemented with data retriever, traditional data pre-processing, several gene-set analysis methods, network visualization and data mining tools...
August 2016: Journal of Bioinformatics and Computational Biology
Yaou Zhao, Mingyan Jiang, Yuehui Chen
This paper demonstrates a new time-delayed mass action model which applies a set of delay differential equations (DDEs) to represent the dynamics of gene regulatory networks (GRNs). The mass action model is a classical model which is often used to describe the kinetics of biochemical processes, so it is fit for GRN modeling. The ability to incorporate time-delayed parameters in this model enables different time delays of interaction between genes. Moreover, an efficient learning method which employs population-based incremental learning (PBIL) algorithm and trigonometric differential evolution (TDE) algorithm TDE is proposed to automatically evolve the structure of the network and infer the optimal parameters from observed time-series gene expression data...
August 2016: Journal of Bioinformatics and Computational Biology
Jin Li, Chengzhen Xu, Lei Wang, Hong Liang, Weixing Feng, Zhongxi Cai, Ying Wang, Wang Cong, Yunlong Liu
Prediction of RNA secondary structures is an important problem in computational biology and bioinformatics, since RNA secondary structures are fundamental for functional analysis of RNA molecules. However, small RNA secondary structures are scarce and few algorithms have been specifically designed for predicting the secondary structures of small RNAs. Here we propose an algorithm named "PSRna" for predicting small-RNA secondary structures using reverse complementary folding and characteristic hairpin loops of small RNAs...
August 2016: Journal of Bioinformatics and Computational Biology
Darlington S Mapiye, Alan G Christoffels, Junaid Gamieldien
Microarray for transcriptomics experiments often suffer from limited statistical power due to small sample size. Quantile discretization (QD) maps expression values for a sample into a series of equivalently sized 'bins' that represent a discrete numerical range, e.g. [Formula: see text]4 to [Formula: see text]4, which enables normalized data from multiple experiments and/or expression platforms to be combined for re-analysis. We found, however, that informal selection of bin numbers often resulted in loss of the underlying correlation structure in the data through assigning of the same numerical value to genes that are in reality expressed at significantly different levels within a sample...
July 13, 2016: Journal of Bioinformatics and Computational Biology
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